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update_test_runs

DestructiveIdempotent

Update fields on test runs in bulk (up to 50). Atomic batch: one bad item rejects entire batch. Set title, status, group_id, or custom fields.

Instructions

Update fields on 1-50 existing test runs in one bulk PATCH; unset fields stay unchanged. Atomic: one bad item rejects the whole batch.

Writable: title, status, group_id, custom_fields. status is validated against the project's testing enumerations. custom_fields is partial; keys are validated against a sample of existing runs, values are not (test runs have no options API). finishedOn is server-managed — not settable. Returns ids only — re-read via list_test_runs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesPer-run changes (1-50); unset fields stay unchanged.
dry_runNoPreview payload without writing; guards still query Polarion.
project_idYesPolarion project ID.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runYes
updatedYes
test_run_idsNo
payload_previewNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate destructive and read/write behavior; the description adds atomicity, validation details, and server-managed fields. No contradiction with annotations. Provides useful behavioral context beyond the structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, no fluff. Front-loaded with the core action and scope. Each sentence adds essential information (scope, atomicity, writable fields, return value). Excellent structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description's mention that it returns IDs only is sufficient. Covers purpose, usage, behavior, parameters, and return. No gaps for this three-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds significant value: lists writable fields, explains validation nuances for status and custom_fields, clarifies that 'finishedOn' is not settable, and elaborates on 'dry_run'. This goes beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action 'Update fields on 1-50 existing test runs in one bulk PATCH', specifying the resource and scope. It distinguishes from siblings like 'update_test_records' and other tools by focusing on test runs and batch operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides solid usage guidance: atomicity, validation rules for status and custom_fields, and that finishedOn is server-managed. It implicitly differentiates from list/get tools. Could be more explicit about when to use vs alternative update tools, but the tool name and context make it clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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